This blog will take a deliberately controversial stance.  In it, I will argue that the discipline and practice of change management will be made redundant by the revolution in digital technologies such as Big Data and Analytics.  The blog will first define what change is, it will briefly review current change approaches, and then explain why big data could make the change management discipline redundant.
So what is Change?
One of the earliest approaches to change was proposed by eminent socialist and psychologist Kurt Lewin.  He stated that for change to occur the driving forces for change must outweigh the resisting forces of change.  Sounds simple enough, but to achieve this the forces of  organisational isomorphism and associated behaviours had to be removed, new behaviour had to be developed to support a desired end state, and these behaviours stabilised and reinforced through supporting mechanisms.  Change can even be expressed as a mathematical equation to demonstrate the struggle between activity and resistance:
C= (ABD)>X
C= Change
A= Level of dissatisfaction with the status quo
B= Desirability of the proposed change or end state
D= Practicality of the change (minimal risk and disruption)
X= Cost of changing
The point that I am trying to make here is that change has often been articulated in terms of ‘current state change future state’.  As such it is revolutionary, and has been articulated as a battle between the forces of change resistance and the forces of change acceptance.
Past Approaches to Change Management
This view of change has orientated the practice of change management toward people centric qualitative approaches, structured as a project to deliver a change.  This qualitative approach has focused on either overcoming change resistance or promoting change acceptance.
Resistance to change is often orientated around people.  Organisational justice with concepts of fairness have caused resistance to change, other factors include the tyranny of custom, and the psychological impact.  Psychologically people fear incompetence and punishment in the newly changed environment, loss of identity, loss of team roles and loss of familiar ways of working.  Thus change management has focused on allieviating these fears through training, communication and transparency.  A second perspective in the current paradigm of change is to try to promote the acceptance of change.  Led by the Harvard guru John Kotter, these change advocates  would argue that people, particularly leaders, can promote the acceptance of change in an organisation through visioning, coalition building, value development, building momentum and communication.
The purpose of this blog is to propose that digitisation has the potential to render the soft approaches above and the change management industry redundant because:

  • The current model focuses on a ‘current state-change-future state’ model and are thus revolutionary.
  • The current model of change takes timeapproaches take time and resource.
  • Change is seen as dangerous and costly.

 Digitisation and Change Management
The Digital revolution itself is a paradigm shifter in the field of change management.  Change will become a quantitative process shifting away from the qualitative people orientated approach.  Change management will be transformed from a state of revolution and combat to one of evolution and collaboration.  Big data and analytics will allow to management closely monitor the external business environment and the behaviour of their customers.  Given real time information there will be no time lag between the business environment change and the required organisational change before a manager can act.  This will allow for the dismissal of the ‘current state – change – future state’ model described above. 
Using the Bid Data and Analytics internally, managers will have a greater oversight and understanding of how their organisations function.  They will be able to improve processes and make tiny process changes incrementally, negating the need for ‘big bang’ communications and employee development processes.  This leads to evolution not revolution.  Indeed the output of individual employees could be monitored, those expressing dissent or not performing in a change aligned way can be fired.  This will remove the people based hubs in the centre of change resistant networks.  In Darwinian terms this suggests rapid genetic engineering, where useless evolutionary traits are rapidly removed and evolutionary change becomes embedded in the organisation.  In an agile organisation where change is constant because of the rapid adaption to new environmental conditions there will be no time for employees to become embedded is the status quo, build internal resistance, thus undermining the ‘current state – change – future state’ model. Without resistance, change becomes easier, with more agility comes less training, and with less resistance comes less need for leadership driven change.  Pro-change employees may even take ownership for change, utilise social media to envision a future and create the guiding coalition making the leader’s role redundant.
Taken to the extreme predictive analytics could provide an organisation with a relatively sure view of the difference each change intervention will make to the organisation.  This would have the effect of taking the risk and the costs out of change management, making change more predictable, less costly and thus more likely to happen on a constant evolutionary basis.
In the past change has been seen as revolutionary, and combatative.  Big data will allow for organisations to evolve rapidly; organisations will become agile and change will become the norm.  There will be no status quo to change from, as a result attitudinal, behavioural and value based change management will become extinct.